1.1

## Warning: Ignoring 1238 observations

According to the countries-and-regions figure of year 2004, America, Japan, Taiwan have the highest density of Aedes albopictus. Central & South America, Southeast and South Asia have the highest density of Aedes aegypti.

## Warning: Ignoring 1238 observations

The situation is changed in 2013, Brazil has the highest density of Aedes aegypti and Taiwan has the highest density of Aedes albopictus.

Evidently, Brazil and Taiwan should consider the spread of mosquitoes in their areas. The countries and regions around Brazil should also take mosquito-spread into their considerations.

1.2

The problem in such plot is that the variance of mosquito population is too large and only several areas have highest density of mosquitoes. Thus, the majority of the plot seems to be colored nothing.

1.3a

After logarithmizing data, the order of severity by mosquito is more evident than before. Most of the countries and regions locate at the middle & low latitudes suffer from mosquitoes.

1.3b

Plot (a) can show the situation of the world more clearly than Plot (b). But plot (b) is much easier for reader to consider the situation of one area in the Northern Hemisphere than plot (a).

1.4

## No scattermapbox mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode
## Warning: Ignoring 1 observations

Depending on the plot, the east coast and south part are the most severely afflicted area in Brazil. But the order of severity is decreasing both from east to west and from south to north.

2.2

Young people have the least incomes (281.1~385.4) compared with Adult (456.4~659.5) and Senior (469.9~683.9). Additionally, most people in each group have lower incomes than the average incomes.

Population with the highest incomes is similar to population with approximately 1.2~1.6 times average incomes. Senior has the largest income variance. Young has the smallest income variance.

2.3

According to the surface, x-axis represents Young, y-axis represents Adult, z-axis represents Senior. Evidently, the incomes of people from different countries locate at the similar position in their age groups, which means people may earn more money if he/she lives in a richer province.

2.4

## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter
## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter

Either for Young or for Adult, the majority with higher incomes live next to Halland and Stockholm. The Young with higher incomes are separated in different proviences equally. On contrary, Adult with low incomes are separated equally, besides Halland and Stockholm.

2.5

## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter